Introduction
Safe and effective vaccines are available that provide strong protection against serious illness, hospitalization and death from COVID-19. Billions of people have been vaccinated against COVID-19. Getting vaccinated protects against COVID-19, helps to end the pandemic and stops new variants emerging.
There are several COVID-19 vaccines validated for use by the World Health Organization. The first mass vaccination programme started in early December 2020. There is some evidence that being fully vaccinated can prevent infection with the COVID-19 virus. This means that being vaccinated is likely to help protect people around you by making it less likely that you will pick up the virus and pass it on.
Research is ongoing to understand the extent to which being vaccinated stops you from becoming infected and passing the virus on to others.
Presentation and description of the problem
This paper focuses on the monthly progress of vaccination in Slovenia since mass vaccination programme, moreover the rate of vaccinated population in Europe will be presented.
Presentation of the data and description of the problem
The data for this project is obtained from kaggle. The dataset is COVID-19 World Vaccination Progress. The dataset is presented below.
## Rows: 86,512
## Columns: 15
## $ country <chr> "Afghanistan", "Afghanistan", "Afg~
## $ iso_code <chr> "AFG", "AFG", "AFG", "AFG", "AFG",~
## $ date <chr> "2021-02-22", "2021-02-23", "2021-~
## $ total_vaccinations <dbl> 0, NA, NA, NA, NA, NA, 8200, NA, N~
## $ people_vaccinated <dbl> 0, NA, NA, NA, NA, NA, 8200, NA, N~
## $ people_fully_vaccinated <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ daily_vaccinations_raw <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ daily_vaccinations <dbl> NA, 1367, 1367, 1367, 1367, 1367, ~
## $ total_vaccinations_per_hundred <dbl> 0.00, NA, NA, NA, NA, NA, 0.02, NA~
## $ people_vaccinated_per_hundred <dbl> 0.00, NA, NA, NA, NA, NA, 0.02, NA~
## $ people_fully_vaccinated_per_hundred <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA~
## $ daily_vaccinations_per_million <dbl> NA, 34, 34, 34, 34, 34, 34, 40, 45~
## $ vaccines <chr> "Johnson&Johnson, Oxford/AstraZene~
## $ source_name <chr> "World Health Organization", "Worl~
## $ source_website <chr> "https://covid19.who.int/", "https~The dataset shows the vaccination rate on global level since the start of the COVID-19 pandemic. For the purpose of this project we decided to narrow down the dataset and focus on the vaccination rate in Europe, moreover a more in depth analysis will be presented for the distributed vaccinates in Slovenia.
Data preparation
In order to continue with the exploratory data analysis we first perform some changes to data formats, and we append a column containing the name of continent.
df3.formatted <- df3 %>% select(Name, Continent)
colnames(df3.formatted)[2] <- "continent"
df1.formatted <- df1 %>%
mutate(date = as.Date(date),
month_char = as.character(date)) %>%
mutate_at(
c(
'people_vaccinated',
'daily_vaccinations_raw',
'daily_vaccinations',
'daily_vaccinations_per_million'
),
as.integer
) %>%
inner_join(df3.formatted, by = c("country" = "Name"))Exploratory data analysis
In the table we can see the percentage of population that is fully immunized and the total number of applied vaccinations per country on global level
immunizations_applied_continent <- df1.formatted %>%
group_by(country) %>%
filter(country != "Gibraltar") %>%
summarise(
population_fully_vaccinated = max(people_fully_vaccinated_per_hundred, na.rm = TRUE),
vaccinations = max(total_vaccinations, na.rm = TRUE), .groups = 'keep'
) %>%
arrange(desc(population_fully_vaccinated))
datatable(immunizations_applied_continent) %>% formatCurrency(
c("vaccinations"),
currency = "",
interval = 3,
mark = ",",
digits = 0
)Immunization by country in Europe
In this section follows a presentation of the vaccination rate in Europe.
Data preparation
immunizations_applied_country <- df1.formatted %>%
group_by(country) %>%
filter(continent=="Europe" & country != "Gibraltar") %>%
summarise(
vaccinations = max(total_vaccinations, na.rm = TRUE),
people_vaccinated = max(people_vaccinated, na.rm = TRUE),
population_vaccinated = max(people_vaccinated_per_hundred, na.rm = TRUE),
population_fully_vaccinated = max(people_fully_vaccinated_per_hundred, na.rm = TRUE),
) %>%
arrange(desc(population_vaccinated)) %>%
mutate(ranking = 1:n())
immunizations_applied_country_temp <- immunizations_applied_country %>%
select(ranking, everything())
colnames(immunizations_applied_country_temp) <-
c(
"ranking",
"country",
"vaccinations",
"people vacinated",
"population vaccinated",
"population fully vaccinated"
)Vaccination progress - population vaccinated
Firstly we can see rate of population that is fully vaccinated in each country
immunizations_applied_country %>%
ggplot(aes(x =reorder(country, -population_fully_vaccinated),
y = population_fully_vaccinated,
label = ceiling(population_fully_vaccinated)))+
geom_bar(aes(fill = population_fully_vaccinated),
position = "identity",
stat = "identity",
show.legend = FALSE)+
labs(x = "Country",
y = "People Fully Vaccinated") +
geom_text(color = "black", vjust = -0.2, size = 4)+
theme_minimal()+
theme(axis.text.x = element_text(angle = 90, hjust = 1, size = 10),
axis.text.y = element_text(hjust = 1.5, lineheight = 20, size = 10)) +
scale_fill_gradient(low = "#164313", high = "#61f756")
From the chart we can conclude that Portugal has the highest vaccination rate, and lowest vaccination rate is in Bosnia and Herzegovina.
Vaccination progress - applied vaccinations
Below we can see the total number of vaccinations vaccines each country distributed.
options(scipen=999)
immunizations_applied_country %>%
ggplot(aes(x = vaccinations,
y = country))+
geom_bar(aes(fill = country),
position = "identity",
stat = "identity",
show.legend = FALSE, ) +
labs(title="Number of vaccines distributed by each country",
x = "Total number of vaccines", y = "Country")+
theme_minimal() +
theme(axis.text.y = element_text(hjust = 1, lineheight = 20, size = 10),
axis.text.x = element_text(vjust = 2,size = 10))
Top 10 ranked countries by vaccinated population
The animation below shows the top 10 ranked countries by vaccinated population for each month since the start of the mass vaccination.
temp <- df1.formatted %>%
filter(continent == "Europe" & country != "Gibraltar") %>%
mutate(country = str_replace(country, "United Kingdom", "UK")) %>%
filter(year(date) >= 2021) %>%
group_by(country, date) %>%
summarise(
vaccinations = max(total_vaccinations, na.rm = TRUE),
people_vaccinated = max(people_vaccinated, na.rm = TRUE),
population_vaccinated = max(people_vaccinated_per_hundred, na.rm = TRUE),
)
ranked_by_year <- temp %>%
group_by(date) %>%
arrange(date, -population_vaccinated) %>%
mutate(rank = 1:n()) %>%
filter(rank <= 10)
my_theme <- theme_classic(base_family = "Times") +
theme(axis.text.y = element_blank()) +
theme(axis.ticks.y = element_blank()) +
theme(axis.line.y = element_blank()) +
theme(legend.background = element_rect(fill = "gainsboro")) +
theme(plot.background = element_rect(fill = "gainsboro")) +
theme(panel.background = element_rect(fill = "gainsboro"))
my_plot <- ranked_by_year %>%
ggplot() +
aes(xmin = 0,
xmax = population_vaccinated) +
aes(ymin = rank - .45,
ymax = rank + .45,
y = rank) +
facet_wrap( ~ ym(date)) +
geom_rect(alpha = .7) +
aes(fill = country) +
scale_fill_viridis_d(option = "magma",
direction = -1) +
scale_x_continuous(limits = c(-80, 550),
breaks = c(0, 25, 50, 75, 100)) +
geom_text(col = "gray13",
hjust = "right",
aes(label = country),
x = -5) +
scale_y_reverse() +
labs(fill = NULL) +
labs(x = 'Population vacinated') +
labs(y = "") +
my_theme
my_plot +
facet_null() +
scale_x_continuous(limits = c(-35, 150),
breaks = c(0, 25, 50, 75, 100)) +
geom_text(
x = 192 ,
y = -10,
family = "Times",
hjust = "right",
aes(label = as.character(date)),
size = 10,
col = "grey18"
) +
aes(group = country) +
gganimate::transition_time(date,) -> animation_plot
animate(animation_plot,
duration = 17,
nframes = 1200,
fps = 20)
Vaccination progress - complete data
More details about the vaccination rate in Europe are shown in the table below
datatable(immunizations_applied_country_temp,
rownames = FALSE) %>% formatCurrency(
c("vaccinations", "people vacinated"),
currency = "",
interval = 3,
mark = ",",
digits = 0
)Immunization in Slovenia
In this section follows a presentation of the vaccination rate in
Slovenia.
Data preparation
immunizations_slov <- immunizations_applied_country_temp %>%
filter(country == "Slovenia")
datatable(immunizations_slov,
rownames = FALSE,
options = list(dom = 't')) %>%
formatCurrency(
c("vaccinations", "people vacinated"),
currency = "",
interval = 3,
mark = ",",
digits = 0
)The table show that Slovenia is on the 33rd place in Europe based on
the vaccinated population.
Monthly vaccination progress
Further we will take a look on the monthly vaccination progress in
Slovenia
slovenia_vaccines <- df1.formatted %>%
group_by(country, month_date = lubridate::floor_date(date, 'month_date')) %>%
filter(country == "Slovenia") %>%
summarise(
vaccinations_monthly = sum(daily_vaccinations, na.rm = TRUE),
people_vaccinated = max(people_vaccinated, na.rm = TRUE),
population_vaccinated = max(people_vaccinated_per_hundred, na.rm = TRUE),
population_fully_vaccinated = max(people_fully_vaccinated_per_hundred, na.rm = TRUE),
) %>%
arrange(month_date)
slovenia_vaccines_temp <- slovenia_vaccines %>%
ungroup() %>%
select(2:6)
colnames(slovenia_vaccines_temp) <-
c(
"month",
"vaccinations",
"people vacinated",
"population vaccinated",
"population fully vaccinated"
)Monthy vaccination progress - population vaccinated
The below chart shows the monthly vaccination progress since the start of the mass vaccination programme in early December 2020
slovenia_vaccines %>%
ggplot()+
geom_line(aes(
x = month_date,
y = people_vaccinated, group = 1), color = "blue", show.legend = FALSE
) +
labs(title = "Montly vaccination rate",
x = "Month",
y = "Number of vaccinated people")+
scale_x_date(date_breaks = "1 months" , date_labels = "%b-%y") +
scale_y_continuous(breaks = seq(0, 1500000, by = 250000), limits = c(0,1264649))+
theme_minimal() +
theme(
axis.text.x = element_text(angle = 45, hjust = 1, size = 10),
axis.text.y = element_text(hjust = 1.4, size = 10)) +
transition_reveal(along = month_date)
From the chart we can conclude that by the end of March 2022 in Slovenia more than 1 250 000 people were vaccinated. We can also see that the number of vaccinated people was continuously rising, moreover there is a rise with a higher rate until September 2021, and after that the vaccination rate is slowing down.
Monthy vaccination progress - applied vaccinations
The below chart shows the total number of vaccinations applied each month since the start of the mass vaccination programme in early December 2020
slovenia_vaccines %>%
ggplot(aes(x = month_date,
y = vaccinations_monthly, label = vaccinations_monthly)) +
geom_bar(
aes(fill = month_date),
position = "identity",
stat = "identity",
show.legend = FALSE
) +
geom_text(color = "blue", vjust = -0.2) +
labs(title = "Number people vaccinated montly",
x = "Month",
y = "Vaccinations") +
scale_x_date(date_breaks = "1 months" , date_labels = "%b-%y") +
theme_minimal() +
theme(
axis.text.x = element_text(angle = 0, hjust = 0.5, size = 10),
axis.text.y = element_text(hjust = 1.5, size = 10)
)
From the chart we can see that the highest number of applied vaccines in Slovenia is in May 2021.
Monthy vaccination progress - complete data
Details on how the vaccination progressed each month are shown in the table below.
datatable(slovenia_vaccines_temp, rownames = FALSE, options = list(pageLength = 8)) %>%
formatCurrency(
c("vaccinations", "people vacinated"),
currency = "",
interval = 3,
mark = ",",
digits = 0
)Conclusion
Based on the results of the exploratory data analysis we conclude that the country with the highest vaccination rate is United Arab Emirates on global level. After narrowing down the data set and focusing on the vaccination rate in Europe, we can conclude that Portugal has the highest vaccination rate, and lowest vaccination rate is in Bosnia and Herzegovina.
On the other hand, for the second part of the analysis, which focuses on the monthly progress of vaccination in Slovenia since mass vaccination programme, the results show that Slovenia’s ranking based on the vaccinated population in Europe is 33. Moreover we conclude that by the end of March 2022 in Slovenia more than 1 250 000 people were vaccinated, which also corresponds to 60.84% of the total population.